Visualization.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "#import lightgbm as lgb\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import log_loss\n",
    "from sklearn import preprocessing\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "\n",
    "%matplotlib inline \n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train = pd.read_csv(\"input/train.txt\", sep=\"\\s+\")\n",
    "test = pd.read_csv(\"input/test.txt\", sep=\"\\s+\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instance_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_category_list</th>\n",
       "      <th>item_property_list</th>\n",
       "      <th>item_brand_id</th>\n",
       "      <th>item_city_id</th>\n",
       "      <th>item_price_level</th>\n",
       "      <th>item_sales_level</th>\n",
       "      <th>item_collected_level</th>\n",
       "      <th>item_pv_level</th>\n",
       "      <th>...</th>\n",
       "      <th>context_page_id</th>\n",
       "      <th>predict_category_property</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>shop_review_num_level</th>\n",
       "      <th>shop_review_positive_rate</th>\n",
       "      <th>shop_star_level</th>\n",
       "      <th>shop_score_service</th>\n",
       "      <th>shop_score_delivery</th>\n",
       "      <th>shop_score_description</th>\n",
       "      <th>is_trade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>108641074714126964</td>\n",
       "      <td>3412720377098676069</td>\n",
       "      <td>7908382889764677758;5799347067982556520</td>\n",
       "      <td>2072967855524022579;5131280576272319091;263639...</td>\n",
       "      <td>1975590437749032870</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>4006</td>\n",
       "      <td>5799347067982556520:-1;509660095530134768:-1;5...</td>\n",
       "      <td>6765930309048922341</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5754713551599725161</td>\n",
       "      <td>3412720377098676069</td>\n",
       "      <td>7908382889764677758;5799347067982556520</td>\n",
       "      <td>2072967855524022579;5131280576272319091;263639...</td>\n",
       "      <td>1975590437749032870</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>5799347067982556520:9172976955054793469;790838...</td>\n",
       "      <td>6765930309048922341</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>842679481291040981</td>\n",
       "      <td>3412720377098676069</td>\n",
       "      <td>7908382889764677758;5799347067982556520</td>\n",
       "      <td>2072967855524022579;5131280576272319091;263639...</td>\n",
       "      <td>1975590437749032870</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>5799347067982556520:5131280576272319091;725801...</td>\n",
       "      <td>6765930309048922341</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>937088850059189027</td>\n",
       "      <td>3412720377098676069</td>\n",
       "      <td>7908382889764677758;5799347067982556520</td>\n",
       "      <td>2072967855524022579;5131280576272319091;263639...</td>\n",
       "      <td>1975590437749032870</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>4016</td>\n",
       "      <td>509660095530134768:-1;5799347067982556520:-1;7...</td>\n",
       "      <td>6765930309048922341</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7975697065017708072</td>\n",
       "      <td>3412720377098676069</td>\n",
       "      <td>7908382889764677758;5799347067982556520</td>\n",
       "      <td>2072967855524022579;5131280576272319091;263639...</td>\n",
       "      <td>1975590437749032870</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>5799347067982556520:9172976955054793469;790838...</td>\n",
       "      <td>6765930309048922341</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           instance_id              item_id  \\\n",
       "0   108641074714126964  3412720377098676069   \n",
       "1  5754713551599725161  3412720377098676069   \n",
       "2   842679481291040981  3412720377098676069   \n",
       "3   937088850059189027  3412720377098676069   \n",
       "4  7975697065017708072  3412720377098676069   \n",
       "\n",
       "                        item_category_list  \\\n",
       "0  7908382889764677758;5799347067982556520   \n",
       "1  7908382889764677758;5799347067982556520   \n",
       "2  7908382889764677758;5799347067982556520   \n",
       "3  7908382889764677758;5799347067982556520   \n",
       "4  7908382889764677758;5799347067982556520   \n",
       "\n",
       "                                  item_property_list        item_brand_id  \\\n",
       "0  2072967855524022579;5131280576272319091;263639...  1975590437749032870   \n",
       "1  2072967855524022579;5131280576272319091;263639...  1975590437749032870   \n",
       "2  2072967855524022579;5131280576272319091;263639...  1975590437749032870   \n",
       "3  2072967855524022579;5131280576272319091;263639...  1975590437749032870   \n",
       "4  2072967855524022579;5131280576272319091;263639...  1975590437749032870   \n",
       "\n",
       "          item_city_id  item_price_level  item_sales_level  \\\n",
       "0  3948283326616421003                 3                 3   \n",
       "1  3948283326616421003                 3                 3   \n",
       "2  3948283326616421003                 3                 3   \n",
       "3  3948283326616421003                 3                 3   \n",
       "4  3948283326616421003                 3                 3   \n",
       "\n",
       "   item_collected_level  item_pv_level    ...     context_page_id  \\\n",
       "0                     4             14    ...                4006   \n",
       "1                     4             14    ...                4001   \n",
       "2                     4             14    ...                4001   \n",
       "3                     4             14    ...                4016   \n",
       "4                     4             14    ...                4001   \n",
       "\n",
       "                           predict_category_property              shop_id  \\\n",
       "0  5799347067982556520:-1;509660095530134768:-1;5...  6765930309048922341   \n",
       "1  5799347067982556520:9172976955054793469;790838...  6765930309048922341   \n",
       "2  5799347067982556520:5131280576272319091;725801...  6765930309048922341   \n",
       "3  509660095530134768:-1;5799347067982556520:-1;7...  6765930309048922341   \n",
       "4  5799347067982556520:9172976955054793469;790838...  6765930309048922341   \n",
       "\n",
       "   shop_review_num_level  shop_review_positive_rate  shop_star_level  \\\n",
       "0                      4                        1.0             5002   \n",
       "1                      4                        1.0             5002   \n",
       "2                      4                        1.0             5002   \n",
       "3                      4                        1.0             5002   \n",
       "4                      4                        1.0             5002   \n",
       "\n",
       "   shop_score_service  shop_score_delivery shop_score_description  is_trade  \n",
       "0                 1.0                  1.0                    1.0         0  \n",
       "1                 1.0                  1.0                    1.0         0  \n",
       "2                 1.0                  1.0                    1.0         0  \n",
       "3                 1.0                  1.0                    1.0         0  \n",
       "4                 1.0                  1.0                    1.0         0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19ec1b72d68>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAD8CAYAAACcjGjIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nOoaDJKnz/wDtS/i00cr5TAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19ec1b3ab38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.item_id.value_counts().hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19ec1e9fb00>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAD4CAYAAAAQP7oXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19ec1eab828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.is_trade.value_counts().plot.bar()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instance_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_category_list</th>\n",
       "      <th>item_property_list</th>\n",
       "      <th>item_brand_id</th>\n",
       "      <th>item_city_id</th>\n",
       "      <th>item_price_level</th>\n",
       "      <th>item_sales_level</th>\n",
       "      <th>item_collected_level</th>\n",
       "      <th>item_pv_level</th>\n",
       "      <th>...</th>\n",
       "      <th>context_page_id</th>\n",
       "      <th>predict_category_property</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>shop_review_num_level</th>\n",
       "      <th>shop_review_positive_rate</th>\n",
       "      <th>shop_star_level</th>\n",
       "      <th>shop_score_service</th>\n",
       "      <th>shop_score_delivery</th>\n",
       "      <th>shop_score_description</th>\n",
       "      <th>is_trade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7972325483281584825</td>\n",
       "      <td>285660928590172217</td>\n",
       "      <td>7908382889764677758;8277336076276184272</td>\n",
       "      <td>2072967855524022579;5131280576272319091;263639...</td>\n",
       "      <td>9057103201734987852</td>\n",
       "      <td>548352491538518780</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>4879721024980945592:2636395404473730413,719936...</td>\n",
       "      <td>4885989684392199728</td>\n",
       "      <td>15</td>\n",
       "      <td>0.985427</td>\n",
       "      <td>5012</td>\n",
       "      <td>0.974878</td>\n",
       "      <td>0.976863</td>\n",
       "      <td>0.969278</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>5698113918818659664</td>\n",
       "      <td>919980016657888153</td>\n",
       "      <td>7908382889764677758;5755694407684602296</td>\n",
       "      <td>5131280576272319091;2636395404473730413;124376...</td>\n",
       "      <td>7066302540842412840</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>19</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>5755694407684602296:9142827274221572643,914848...</td>\n",
       "      <td>6597981382309269962</td>\n",
       "      <td>21</td>\n",
       "      <td>0.997040</td>\n",
       "      <td>5018</td>\n",
       "      <td>0.979661</td>\n",
       "      <td>0.979589</td>\n",
       "      <td>0.975442</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>3398773118902833938</td>\n",
       "      <td>557883074900282934</td>\n",
       "      <td>7908382889764677758;8277336076276184272</td>\n",
       "      <td>2636395404473730413;6434796455031995313;643479...</td>\n",
       "      <td>7066302540842412840</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>19</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>8277336076276184272:2636395404473730413;176016...</td>\n",
       "      <td>6597981382309269962</td>\n",
       "      <td>21</td>\n",
       "      <td>0.997040</td>\n",
       "      <td>5018</td>\n",
       "      <td>0.979661</td>\n",
       "      <td>0.979589</td>\n",
       "      <td>0.975442</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>8127284011992533394</td>\n",
       "      <td>1093710751022752245</td>\n",
       "      <td>7908382889764677758;5755694407684602296</td>\n",
       "      <td>5131280576272319091;2636395404473730413;101341...</td>\n",
       "      <td>7066302540842412840</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>19</td>\n",
       "      <td>...</td>\n",
       "      <td>4012</td>\n",
       "      <td>509660095530134768:2636395404473730413;8277336...</td>\n",
       "      <td>6597981382309269962</td>\n",
       "      <td>21</td>\n",
       "      <td>0.997040</td>\n",
       "      <td>5018</td>\n",
       "      <td>0.979661</td>\n",
       "      <td>0.979589</td>\n",
       "      <td>0.975442</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>7059890618965359082</td>\n",
       "      <td>2540781378235236842</td>\n",
       "      <td>7908382889764677758;8277336076276184272</td>\n",
       "      <td>2072967855524022579;2636395404473730413;124376...</td>\n",
       "      <td>7066302540842412840</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>...</td>\n",
       "      <td>4001</td>\n",
       "      <td>8277336076276184272:2636395404473730413;176016...</td>\n",
       "      <td>6597981382309269962</td>\n",
       "      <td>21</td>\n",
       "      <td>0.997040</td>\n",
       "      <td>5018</td>\n",
       "      <td>0.979661</td>\n",
       "      <td>0.979589</td>\n",
       "      <td>0.975442</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             instance_id              item_id  \\\n",
       "14   7972325483281584825   285660928590172217   \n",
       "52   5698113918818659664   919980016657888153   \n",
       "55   3398773118902833938   557883074900282934   \n",
       "83   8127284011992533394  1093710751022752245   \n",
       "129  7059890618965359082  2540781378235236842   \n",
       "\n",
       "                          item_category_list  \\\n",
       "14   7908382889764677758;8277336076276184272   \n",
       "52   7908382889764677758;5755694407684602296   \n",
       "55   7908382889764677758;8277336076276184272   \n",
       "83   7908382889764677758;5755694407684602296   \n",
       "129  7908382889764677758;8277336076276184272   \n",
       "\n",
       "                                    item_property_list        item_brand_id  \\\n",
       "14   2072967855524022579;5131280576272319091;263639...  9057103201734987852   \n",
       "52   5131280576272319091;2636395404473730413;124376...  7066302540842412840   \n",
       "55   2636395404473730413;6434796455031995313;643479...  7066302540842412840   \n",
       "83   5131280576272319091;2636395404473730413;101341...  7066302540842412840   \n",
       "129  2072967855524022579;2636395404473730413;124376...  7066302540842412840   \n",
       "\n",
       "            item_city_id  item_price_level  item_sales_level  \\\n",
       "14    548352491538518780                 8                 9   \n",
       "52   3948283326616421003                 7                11   \n",
       "55   3948283326616421003                 7                12   \n",
       "83   3948283326616421003                 7                11   \n",
       "129  3948283326616421003                 7                14   \n",
       "\n",
       "     item_collected_level  item_pv_level    ...     context_page_id  \\\n",
       "14                      8             13    ...                4001   \n",
       "52                     12             19    ...                4001   \n",
       "55                     14             19    ...                4001   \n",
       "83                     12             19    ...                4012   \n",
       "129                    15             20    ...                4001   \n",
       "\n",
       "                             predict_category_property              shop_id  \\\n",
       "14   4879721024980945592:2636395404473730413,719936...  4885989684392199728   \n",
       "52   5755694407684602296:9142827274221572643,914848...  6597981382309269962   \n",
       "55   8277336076276184272:2636395404473730413;176016...  6597981382309269962   \n",
       "83   509660095530134768:2636395404473730413;8277336...  6597981382309269962   \n",
       "129  8277336076276184272:2636395404473730413;176016...  6597981382309269962   \n",
       "\n",
       "     shop_review_num_level  shop_review_positive_rate  shop_star_level  \\\n",
       "14                      15                   0.985427             5012   \n",
       "52                      21                   0.997040             5018   \n",
       "55                      21                   0.997040             5018   \n",
       "83                      21                   0.997040             5018   \n",
       "129                     21                   0.997040             5018   \n",
       "\n",
       "     shop_score_service  shop_score_delivery shop_score_description  is_trade  \n",
       "14             0.974878             0.976863               0.969278         1  \n",
       "52             0.979661             0.979589               0.975442         1  \n",
       "55             0.979661             0.979589               0.975442         1  \n",
       "83             0.979661             0.979589               0.975442         1  \n",
       "129            0.979661             0.979589               0.975442         1  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_istrade = train[train.is_trade == 1]\n",
    "train_istrade.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19ec1fac0f0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYEAAAD8CAYAAACRkhiPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYf8Lwdit4GJ7fEIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19ec1ecc2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_istrade.item_id.value_counts().hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instance_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_category_list</th>\n",
       "      <th>item_property_list</th>\n",
       "      <th>item_brand_id</th>\n",
       "      <th>item_city_id</th>\n",
       "      <th>item_price_level</th>\n",
       "      <th>item_sales_level</th>\n",
       "      <th>item_collected_level</th>\n",
       "      <th>item_pv_level</th>\n",
       "      <th>...</th>\n",
       "      <th>context_timestamp</th>\n",
       "      <th>context_page_id</th>\n",
       "      <th>predict_category_property</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>shop_review_num_level</th>\n",
       "      <th>shop_review_positive_rate</th>\n",
       "      <th>shop_star_level</th>\n",
       "      <th>shop_score_service</th>\n",
       "      <th>shop_score_delivery</th>\n",
       "      <th>shop_score_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2475218615076601065</td>\n",
       "      <td>2275895163219263378</td>\n",
       "      <td>7908382889764677758;8277336076276184272</td>\n",
       "      <td>2636395404473730413;7515802706813700848;302719...</td>\n",
       "      <td>7838285046767229711</td>\n",
       "      <td>7534238860363577544</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>1537885700</td>\n",
       "      <td>4005</td>\n",
       "      <td>8277336076276184272:-1;5799347067982556520:-1;...</td>\n",
       "      <td>5275548996133547595</td>\n",
       "      <td>13</td>\n",
       "      <td>0.985244</td>\n",
       "      <td>5011</td>\n",
       "      <td>0.964023</td>\n",
       "      <td>0.966550</td>\n",
       "      <td>0.955378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>398316874173557226</td>\n",
       "      <td>7096238490711246967</td>\n",
       "      <td>7908382889764677758;5755694407684602296</td>\n",
       "      <td>5131280576272319091;2636395404473730413;734498...</td>\n",
       "      <td>8126195666233054089</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>1537862843</td>\n",
       "      <td>4001</td>\n",
       "      <td>5755694407684602296:216555019471416386,2636395...</td>\n",
       "      <td>329470548383752413</td>\n",
       "      <td>14</td>\n",
       "      <td>0.989068</td>\n",
       "      <td>5012</td>\n",
       "      <td>0.963794</td>\n",
       "      <td>0.964225</td>\n",
       "      <td>0.959134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6586402638209028583</td>\n",
       "      <td>7096238490711246967</td>\n",
       "      <td>7908382889764677758;5755694407684602296</td>\n",
       "      <td>5131280576272319091;2636395404473730413;734498...</td>\n",
       "      <td>8126195666233054089</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>1537858222</td>\n",
       "      <td>4011</td>\n",
       "      <td>5755694407684602296:2636395404473730413;871073...</td>\n",
       "      <td>329470548383752413</td>\n",
       "      <td>14</td>\n",
       "      <td>0.989068</td>\n",
       "      <td>5012</td>\n",
       "      <td>0.963794</td>\n",
       "      <td>0.964225</td>\n",
       "      <td>0.959134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1040996105851528465</td>\n",
       "      <td>7096238490711246967</td>\n",
       "      <td>7908382889764677758;5755694407684602296</td>\n",
       "      <td>5131280576272319091;2636395404473730413;734498...</td>\n",
       "      <td>8126195666233054089</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>1537860915</td>\n",
       "      <td>4001</td>\n",
       "      <td>8710739180200009128:-1;5755694407684602296:263...</td>\n",
       "      <td>329470548383752413</td>\n",
       "      <td>14</td>\n",
       "      <td>0.989068</td>\n",
       "      <td>5012</td>\n",
       "      <td>0.963794</td>\n",
       "      <td>0.964225</td>\n",
       "      <td>0.959134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6316278569655873454</td>\n",
       "      <td>7096238490711246967</td>\n",
       "      <td>7908382889764677758;5755694407684602296</td>\n",
       "      <td>5131280576272319091;2636395404473730413;734498...</td>\n",
       "      <td>8126195666233054089</td>\n",
       "      <td>3948283326616421003</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>1537859074</td>\n",
       "      <td>4001</td>\n",
       "      <td>5755694407684602296:5131280576272319091;871073...</td>\n",
       "      <td>329470548383752413</td>\n",
       "      <td>14</td>\n",
       "      <td>0.989068</td>\n",
       "      <td>5012</td>\n",
       "      <td>0.963794</td>\n",
       "      <td>0.964225</td>\n",
       "      <td>0.959134</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           instance_id              item_id  \\\n",
       "0  2475218615076601065  2275895163219263378   \n",
       "1   398316874173557226  7096238490711246967   \n",
       "2  6586402638209028583  7096238490711246967   \n",
       "3  1040996105851528465  7096238490711246967   \n",
       "4  6316278569655873454  7096238490711246967   \n",
       "\n",
       "                        item_category_list  \\\n",
       "0  7908382889764677758;8277336076276184272   \n",
       "1  7908382889764677758;5755694407684602296   \n",
       "2  7908382889764677758;5755694407684602296   \n",
       "3  7908382889764677758;5755694407684602296   \n",
       "4  7908382889764677758;5755694407684602296   \n",
       "\n",
       "                                  item_property_list        item_brand_id  \\\n",
       "0  2636395404473730413;7515802706813700848;302719...  7838285046767229711   \n",
       "1  5131280576272319091;2636395404473730413;734498...  8126195666233054089   \n",
       "2  5131280576272319091;2636395404473730413;734498...  8126195666233054089   \n",
       "3  5131280576272319091;2636395404473730413;734498...  8126195666233054089   \n",
       "4  5131280576272319091;2636395404473730413;734498...  8126195666233054089   \n",
       "\n",
       "          item_city_id  item_price_level  item_sales_level  \\\n",
       "0  7534238860363577544                 7                 6   \n",
       "1  3948283326616421003                 6                 9   \n",
       "2  3948283326616421003                 6                 9   \n",
       "3  3948283326616421003                 6                 9   \n",
       "4  3948283326616421003                 6                 9   \n",
       "\n",
       "   item_collected_level  item_pv_level           ...            \\\n",
       "0                     8             14           ...             \n",
       "1                     8             16           ...             \n",
       "2                     8             16           ...             \n",
       "3                     8             16           ...             \n",
       "4                     8             16           ...             \n",
       "\n",
       "   context_timestamp  context_page_id  \\\n",
       "0         1537885700             4005   \n",
       "1         1537862843             4001   \n",
       "2         1537858222             4011   \n",
       "3         1537860915             4001   \n",
       "4         1537859074             4001   \n",
       "\n",
       "                           predict_category_property              shop_id  \\\n",
       "0  8277336076276184272:-1;5799347067982556520:-1;...  5275548996133547595   \n",
       "1  5755694407684602296:216555019471416386,2636395...   329470548383752413   \n",
       "2  5755694407684602296:2636395404473730413;871073...   329470548383752413   \n",
       "3  8710739180200009128:-1;5755694407684602296:263...   329470548383752413   \n",
       "4  5755694407684602296:5131280576272319091;871073...   329470548383752413   \n",
       "\n",
       "   shop_review_num_level  shop_review_positive_rate  shop_star_level  \\\n",
       "0                     13                   0.985244             5011   \n",
       "1                     14                   0.989068             5012   \n",
       "2                     14                   0.989068             5012   \n",
       "3                     14                   0.989068             5012   \n",
       "4                     14                   0.989068             5012   \n",
       "\n",
       "   shop_score_service shop_score_delivery  shop_score_description  \n",
       "0            0.964023            0.966550                0.955378  \n",
       "1            0.963794            0.964225                0.959134  \n",
       "2            0.963794            0.964225                0.959134  \n",
       "3            0.963794            0.964225                0.959134  \n",
       "4            0.963794            0.964225                0.959134  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "select_cols = ['item_price_level','item_sales_level','item_collected_level','item_pv_level','user_gender_id','user_age_level','user_star_level','context_page_id',\n",
    "              'shop_review_num_level','shop_review_positive_rate','shop_star_level','shop_score_service','shop_score_delivery','shop_score_description']\n",
    "\n",
    "select_train = train[select_cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_price_level</th>\n",
       "      <th>item_sales_level</th>\n",
       "      <th>item_collected_level</th>\n",
       "      <th>item_pv_level</th>\n",
       "      <th>user_gender_id</th>\n",
       "      <th>user_age_level</th>\n",
       "      <th>user_star_level</th>\n",
       "      <th>context_page_id</th>\n",
       "      <th>shop_review_num_level</th>\n",
       "      <th>shop_review_positive_rate</th>\n",
       "      <th>shop_star_level</th>\n",
       "      <th>shop_score_service</th>\n",
       "      <th>shop_score_delivery</th>\n",
       "      <th>shop_score_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>1003</td>\n",
       "      <td>3003</td>\n",
       "      <td>4006</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>1002</td>\n",
       "      <td>3006</td>\n",
       "      <td>4001</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>1003</td>\n",
       "      <td>3004</td>\n",
       "      <td>4001</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>1004</td>\n",
       "      <td>3006</td>\n",
       "      <td>4016</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>1002</td>\n",
       "      <td>3001</td>\n",
       "      <td>4001</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5002</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_price_level  item_sales_level  item_collected_level  item_pv_level  \\\n",
       "0                 3                 3                     4             14   \n",
       "1                 3                 3                     4             14   \n",
       "2                 3                 3                     4             14   \n",
       "3                 3                 3                     4             14   \n",
       "4                 3                 3                     4             14   \n",
       "\n",
       "   user_gender_id  user_age_level  user_star_level  context_page_id  \\\n",
       "0               1            1003             3003             4006   \n",
       "1               0            1002             3006             4001   \n",
       "2               0            1003             3004             4001   \n",
       "3               1            1004             3006             4016   \n",
       "4               0            1002             3001             4001   \n",
       "\n",
       "   shop_review_num_level  shop_review_positive_rate  shop_star_level  \\\n",
       "0                      4                        1.0             5002   \n",
       "1                      4                        1.0             5002   \n",
       "2                      4                        1.0             5002   \n",
       "3                      4                        1.0             5002   \n",
       "4                      4                        1.0             5002   \n",
       "\n",
       "   shop_score_service  shop_score_delivery  shop_score_description  \n",
       "0                 1.0                  1.0                     1.0  \n",
       "1                 1.0                  1.0                     1.0  \n",
       "2                 1.0                  1.0                     1.0  \n",
       "3                 1.0                  1.0                     1.0  \n",
       "4                 1.0                  1.0                     1.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training...\n"
     ]
    }
   ],
   "source": [
    "#from sklearn import linear_model\n",
    "#from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.svm import SVC\n",
    "X = train[select_cols]\n",
    "Y = train['is_trade']\n",
    "\n",
    "X_train,X_test,y_train,y_test = train_test_split(X,Y,test_size=0.4, random_state=0)\n",
    "# This is your model that will learn to predict\n",
    "#model = RandomForestRegressor()\n",
    "model = SVC()\n",
    "print(\"Training...\")\n",
    "# Your model is trained on the training_data\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "print(\"Predicting...\")\n",
    "# Your trained model is now used to make predictions on the numerai_tournament_data\n",
    "# The model returns two columns: [probability of 0, probability of 1]\n",
    "# We are just interested in the probability that the target is 1.\n",
    "y_prediction = model.predict_proba(X_test)\n",
    "test_pred = y_prediction[:, 1]\n",
    "print('误差 ', log_loss(y_test, test_pred))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}